Knowledge as a concept and knowledge management strategy . 42

Before discussing knowledge management, the subject, i.e., knowledge itself, will be discussed in this section. In a continuum starting from data, then information, and ending with knowledge, knowledge is seen to be the most valuable as data consists of simple facts which can be structured to become information, and information becomes knowledge when it is interpreted, put into context, or when it has meaning added to it (Grover and Davenport, 2001). In other words, knowledge is created from information and is closely related to a person's beliefs and commitments (Nonaka, 1994). As a multi-faceted concept, knowledge has been defined from different perspectives and with different focuses (Alavi and Leidner, 2001). Reviewing various definitions of knowledge in the extant literature, knowledge could be defined as a state of mind, an object, a process, a capability, or a condition of having access to information (Alavi and Leidner, 2001). As a state of mind, knowledge is an understanding through experience or learning; as an object, knowledge can be used, stored, and manipulated to suit the needs of the company;

as a process, knowledge is the application of one’s experience; as a capability, knowledge is the ability of knowing how to use information to influence future action; as a condition of having access to information, knowledge focuses on the way to organize access and retrieve the information in the company (Alavi and Leidner, 2001). In the current study, by considering the interpretation and contextualization of information (Davenport and Pruzak, 2000; Nissen, 2006), knowledge is defined as “a justified belief that increases the entity’s capacity for taking effective action” (Alavi and Leidner, 2001, p.109).

One of the most widely acknowledged categories of knowledge is the distinction between explicit and tacit knowledge (Nonaka, 1994; Nonaka et al., 2000; Nonaka and Von Krogh, 2009; Polanyi, 1966), which reflect the status of knowledge (Mesmer-Magnus and Dechurch, 2012). Explicit knowledge refers to knowledge outside the human mind that can be expressed in formal and systematic language, be codified and stored in words, documents or other explicit forms, and can be captured and shared in records such as databases and archives (Nonaka, 1994; Nonaka et al., 2000). Explicit knowledge comprises data, formulae, manuals, drawings, and specifications etc. which can be processed, transmitted, shared, and stored relatively easily (Nonaka et al., 2000).

However, explicit knowledge can only show the tip of the iceberg of what someone knows

(Nonaka, 1994), and ‘we can know more than we can tell’ due to the tacit nature of knowledge (Polanyi, 1966, p. 4). Frist introduced by Polanyi (1966), tacit knowledge refers to knowledge indwelling in the person’s mind that is difficult or sometimes even impossible to formalize and articulate (Nonaka, 1994; Nonaka et al., 2000). The time required to explain and learn tacit knowledge slows down its transfer (Argote, 2013). The more tacit the knowledge is, the more difficult it is to articulate, and the greater interaction and socialization between individuals is required to make the transfer successful (Hansen, 1999).

Explicit and tacit knowledge are dependent on each other, which makes it difficult to identify the most valuables between these two types of knowledge (Nonaka, 1994). In order to understand explicit knowledge, tacit knowledge is a necessity (Alavi and Leidner, 2001). Without explicit knowledge, tacit knowledge is meaningless (Sánchez, Sánchez, Ruiz, and Tarrasóna, 2012). In addition, these two types of knowledge can be converted to each other through different processes in a classic SECI model for knowledge creation (Nonaka, 1994; Nonaka et al., 2000), i.e., socialization, externalization, combination, and internalization. Movement through the four knowledge conversion modes forms a spiral and dynamic process of knowledge creation taking place both intra- and inter-organizationally, where the interaction between tacit knowledge and explicit knowledge is amplified (Nonaka, 1994; Nonaka et al., 2000).

Knowledge can also be categorized based on its functions or related discipline, such as design knowledge (e.g. product design, process design, service design, service operation design, etc.), product knowledge, task knowledge (e.g., design task, logistics task, etc.), production/manufacturing knowledge, customer knowledge, and market knowledge, etc.

(Baxter et al. 2009; Zhang et al., 2012).

It is important to describe the types of knowledge for further analysis, for instance to identify which type of knowledge is most important in a company, or in a special context.

However, the previously described categories or distinctions are not independent, rather their scope of definition may overlap in various ways. Knowledge can be described as one or several categories.

Knowledge management – the process view and strategy

From the KBV’s perspective, knowledge management enables an organization to be capable of utilizing and developing knowledge resources to create a competitive advantage, and thus it represents the capability- and activity-oriented aspects of the KBV (Kogut and Zander, 1992; Grant, 1996; Spender, 1996). Organizations in various industries have invested heavily in knowledge management initiatives (i.e. Dyer and Nobeoka, 2000; Ezingeard, Leigh, and Chandler-Wilde, 2000; Jang, Hong, Bock, and Kim, 2002; Massey, Montoya-Weiss, and O'Driscoll, 2002). Some organizations, such as Boeing, IBM, and Siemens, have achieved great success from their knowledge management investments (Rao, 2012). However, knowledge management expenditures are not necessarily proportional to the gains obtained. Numerous knowledge management

initiatives have failed to achieve the desired results (Malhotra, 2004). Quite a few companies are still struggling with low returns on knowledge management investments (Chai and Nebus, 2012; Rao, 2012;). Therefore, finding a more systematic way to manage knowledge management initiatives has become an urgent issue for both academia and industry.

Given the importance and complexity of knowledge management, researchers have investigated it in various disciplines (Wang and Noe, 2010). To better understand the concept and key points of knowledge management, some definitions in the extant literature are listed in Table 2.

Table 2. Definitions and key points of knowledge management

Reference Definition Key points

Alavi and Leidner, 1999

Knowledge management is a systematic and organizationally specified process to acquire, organize, and communicate employees’ knowledge so that other employees can use this knowledge to improve work efficiency and productivity.

Process

Acquisition, sharing, and application/reuse

Alavi and Leidner, 2001

Knowledge management is regarded as a process to a large extent, involving at least four basic processes of creating, storing/retrieving, transferring and applying knowledge.

Process

Creation, storage/retrieval, transfer, and application Argote, 2003 Knowledge management research focuses on the

“fundamental set of questions” relating to knowledge creation, retention and transfer within and across companies, as well as the management of company’s knowledge reserves.

Process + practice Creation, retention, and transfer

Bemret and Bennetz, 2003

Knowledge management is a systematic process of creating, maintaining, and cultivating an organization to fully utilize its knowledge to realize its vision, which is broadly regarded as a sustainable competitive advantage or achieving high performance.

Process

Creation, maintain, cultivation, and application / reuse

Hislop, 2009 Knowledge management is the processes in an organization related to knowledge acquisition, codification, sharing, creation, and application.

Process

Acquisition, codification, sharing, creation, and application

Janz and Prasarnphanic h, 2003

Knowledge management is an organizational strategy to manage the development, flow, and application of

Knowledge management is the process of efficiently capturing, sharing, developing, and using the knowledge.

Process

Capturing, sharing, development, and use (application)

Scarborough, Swan, and Preston, 1999

Knowledge management refers to the process of creating, acquiring, sharing, and using knowledge to enhance learning and performance in an organization.

Process

Creation, acquisition, sharing, and application Swan, Newell,

Scarbrough, and Hislop, 1999

Knowledge management concerns any processes and practices related to the creation, acquisition, sharing and use of knowledge, skills and expertise.

Process + practice Creation, acquisition, sharing, and application

As an umbrella term, knowledge management refers to the deliberate efforts focused on the management of knowledge of a firm (Hislop, 2009). Despite the diversity of processes or practices when enumerating knowledge management, such as knowledge acquisition, sharing, transfer, flow (movement), codification, storage/retrieval,, retention, maintain, development, cultivation, creation, and application/reuse (as shown in Table 2), the process view of knowledge management in its most simplistic form basically comprises three broad intertwined stages: knowledge creation, transfer/sharing, and application/reuse. Knowledge creation refers to the development of new content or the replacement of already existing content within a firm’s knowledge, both tacit and explicit (Alavi and Leidner, 2001). Knowledge transfer refers to process through which one social unit learns from or is influenced by the experience of another unit (Argote, 2013; Argote and Fahrenkopf, 2016). Broadly, this involves both knowledge sharing and knowledge reuse (Wang and Neo, 2010). Knowledge application is the process of knowledge utilization. Especially, the ability to gain competitive advantage is more about applying existing knowledge to take action than the knowledge itself (Grant, 1996), indicating the importance of knowledge reuse.

Knowledge creation is generally regarded as more important and more difficult to manage. However, as indicated in the literature, the low returns on knowledge management initiatives has mostly been due to failing to share and reuse knowledge (Majchrzak, Wagner, and Yates, 2013; Wang and Neo, 2010). Therefore, a better understanding of knowledge sharing and reuse in a company is needed to improve returns on knowledge management investments, which motivated the author to narrow the focus of knowledge management to particular processes, i.e., knowledge sharing and knowledge reuse, which will be discussed in detail in section 2.2.3.

Further building on the importance of knowledge sharing and knowledge reuse, studies have also been conducted on knowledge management strategies to understand how knowledge sharing and reuse has performed. Codification and personalization are two types of knowledge management strategies in a broad sense (Hansen, Nohria, and Tierney, 1999). In the codification strategy, knowledge is codified and stored so that potential consumers/users can reuse it without necessarily knowing the knowledge producer. It is a ‘people-to-document’ approach to separate knowledge from the person

and focuses on the use of technology, such as databases, electronic repositories, and decision support systems, etc. In contrast, in the personalization strategy, there are direct interactions between knowledge producers and the potential knowledge consumers of knowledge communication, i.e., through face-to-face communication, such as on-the-job learning, storytelling, training activities and communities of practice (Brown and Duguid, 2001). It is a ‘people-to-people’ approach that facilitates interactions among people through networks, where knowledge is tied to a person and may remain tacit.

Codification and personalization strategies are associated with different costs and benefits, which make it challenging for organizations to develop an optimum knowledge management strategy. The codification strategy requires companies to invest in electronic repositories and knowledge must be codified by the producers before knowledge reuse takes place, whereas the cost involved in the personalization strategy is incurred mostly when knowledge reuse takes place and is proportional to the number of potential knowledge consumers (Chai and Nebus, 2012). In the codification strategy, a large number of people can access a standardized repository simultaneously, whereas only a limited number of people can be reached in the personalization strategy although rich information can be conveyed (Chai, Gregory, and Shi, 2003). In addition, potential consumers can retrieve knowledge from a repository whenever they need it, whereas whether they can obtain knowledge from the knowledge producers depends on the availability of that particular person (Lee and Van den Steen, 2010). The codification strategy can only transfer explicit knowledge, whereas the personalization strategy can transfer both explicit and tacit knowledge (Hahn and Mukherjee, 2007). However, due to the dramatically increased cost of knowledge codification incurred by the increased tacitness of knowledge, firms prefer to keep the tacit form of knowledge (Jasimuddin and Zhang, 2009).

Despite extensive research on the choice of strategies between codification and personalization, not many consistent results or recommendations could be found in the literature. In their pioneering and highly cited work proposing the classification of codification and personalization strategies, Hansen, Nohria and Tierney (1999) found that it was not an optimal choice to adopt a single strategy or to use two strategies simultaneously with the same effort. Rather, they found that companies should choose a knowledge management strategy based on their products’ characteristics and their employees’ working needs. It would be better to use one strategy predominantly (e.g., 80%) and use the other one in a supporting role (e.g., 20%), which was supported by their findings from management consulting firms, computer companies, and healthcare providers (Hansen et al., 1999). However, a balanced 50-50 split between the two strategies has been found to be preferred in certain industries such as the pharmaceutical industry (Koenig, 2001) and in certain organizations such as NASA (Moll, 2019). In order to reconcile these contradictory views, some researchers have pointed out that companies may need to evolve their knowledge management strategies by adding a temporal dimension and adjusting the proportion of codification and personalization to align with the various stages of knowledge management, i.e., to adopt one strategy predominantly at the beginning and move towards a balanced portfolio as it matures (Scheepers,

Venkitachalam, and Gibbs, 2004). A case study in NASA confirmed this view, which showed that NASA’s knowledge management strategy evolved from an emphasis on a personalization strategy in the 1980s which changed to an emphasis on a codification strategy in the 1990s, and finally had adopted a balanced approach since around 2012. No detrimental effects on NASA’s performance had been found since adopting this balanced approach (Moll, 2019).

The discussions above revealed that both codification and personalization strategies should be adopted by complementing each other to achieve the focused objectives of the company (Powell and Ambrosini, 2012). However, no conclusive guidelines on the mix ratio could be found in the literature and the studies were from different industries without any focus on a PSS context, which motivated the author to investigate knowledge management strategies and practices in the PSS context. Considering the various stakeholders, entire lifecycle concerns, and multi-disciplinary knowledge required in the PSS context would provide insight to both PSS and knowledge management research.

2.2.3 Knowledge sharing and knowledge reuse – definition and mechanisms Broadly speaking, knowledge sharing, knowledge reuse, and knowledge transfer refer to the same process of knowledge movement (Argote, 2013; Argote and Fahrenkopf, 2016;

Argote and Ingram 2000; Davenport and Prusak, 2000; Majchrzak et al., 2004; Markus, 2001; Szulanski, 1996; Van den Hooff and De Leeuw van Weenen, 2004; Wang and Neo, 2010). Generally, there are two parties involved in the knowledge movement process: the knowledge sender/contributor/producer, which refers to the roles of employees when they have knowledge to share with others; and the knowledge recipient or potential consumer/user, which refers to the roles of employees when they try to seek and use knowledge from others (Szulanski 1996; Alavi and Leidner 2001). To make the knowledge movement successful, effective and efficient transmission channels, i.e., the mechanisms, are necessary (Gupta and Govindarajan, 2000).

Wang and Neo (2010) defined knowledge sharing as the provision of task information and know-how to help and to collaborate with others with the objective of problem solving, the development of new ideas, or the implementation of policies/procedures . Compared to that, Davenport and Prusak (2000) defined knowledge sharing as a two-way process, including both the provision and receipt of task information and know-how concerning a product or a procedure. Similar to the definition from Davenport and Prusak (2000), the knowledge sharing process proposed by Van den Hooff and De Leeuw van Weenen (2004) contains knowledge donation and knowledge collection, in which donation occurs when a sender shares knowledge with others. This is similar to knowledge sharing defined by Wang and Neo (2010), whereas collection takes place when a recipient gathers knowledge from others. In addition, in their definition, knowledge reuse is also included in knowledge collection (Van den Hooff and De Leeuw van Weenen, 2004).

Defined by Markus (2001), knowledge reuse is a process with four stages, including knowledge capture or documentation, knowledge packaging for reuse (processing documents in accordance with the classification scheme), knowledge distribution or dissemination (providing people with access to it), and knowledge reuse (recall from where the required knowledge is and the actual application of it), as shown in Figure 5.

In particular, this process highlighted the importance of knowledge capture and packaging of the existing knowledge, which is from the knowledge recipient’s perspective. In addition, it was found that an IT-focus was crucial in knowledge reuse, especially concerning knowledge storage and retrieval (Markus, 2001).

Figure 5. Knowledge reuse process (adapted from Markus, 2001)

More focused on the understanding of knowledge reuse for innovation, Majchrzak, Cooper and Neece (2004) proposed a different knowledge reuse process with three main stages, where stage one focuses on reconceptualizing the problem which needs to be solved for innovation, stage two concerns searching and evaluating existing knowledge within or outside the company to select a usable one, and stage three is the actual acquisition of the knowledge and full application into a final solution, as shown in Figure 6. Compared to the process proposed by Markus (2001), the process proposed by Majchrzak et al. (2004) paid more attention to the search and actual use of the existing shared knowledge from the knowledge recipient’s perspective.

Figure 6. Knowledge reuse process for innovation (source: Majchrzak, et al., 2004)

Briefly Evaluation

Analyze In  Depth

Scan Fully

Develop

Decide to  Search Reconceptualize

Problem for  Innovation

Search and Evaluate

Experience  insurmountable  performance  gap Awareness of traditional 

and nontraditional

Conduct  broad,  nontraditional  search

Awareness that meta‐knowledge

exists

Access to  metaknowledge

Shared  experience with 

adapter

Compared to knowledge sharing and knowledge reuse, knowledge transfer refers to a process through which one social unit learns from or is influenced by the experience of another unit (Argote, 2013; Argote and Fahrenkopf, 2016), i.e., knowledge acquired in one situation is applied to another situation (Argote and Ingram 2000; Szulanski, 1996).

Therefore, as a process, knowledge transfer comprises both knowledge sharing and knowledge reuse (Alavi and Leidner, 2001; Appleyard, 1996).

Knowledge sharing, knowledge reuse, and knowledge transfer are intertwined concepts, but with a different emphasis and from different perspectives. Knowledge sharing typically emphasizes the sender’s contribution to knowledge (i.e., their knowledge contribution) from a supplier’s (sender’s) perspective; knowledge reuse focuses on the demand for knowledge from a consumer’s (recipient’s) perspective (i.e. knowledge seeking and reuse), and knowledge transfer emphasizes the efficacy of knowledge movement between the predetermined sender and recipient (i.e. the effective and efficient transfer) (Gray and Meister, 2004; Majchrzak et al., 2004; Szulanski, 1996; Wang and Neo, 2010). As two interrelated and inseparable knowledge management processes, knowledge sharing (i.e., knowledge contributing) and knowledge reuse (i.e., knowledge seeking and reuse) are associated with different needs (Kankanhalli et al., 2005; Watson and Hewett, 2006). However, little research has been conducted to investigate both knowledge sharing and knowledge reuse systematically (He and Wei, 2009). Based on this, knowledge sharing and knowledge reuse will be the emphasized areas in this thesis.

Considering the relationships and difference between these two processes, knowledge transfer in this thesis will be treated as a stage covered by both knowledge sharing and knowledge reuse processes (Majchrzak et al., 2004; Markus, 2001; Szulanski, 2000).

Therefore, this thesis will further explore knowledge sharing and knowledge reuse from the sender’s and the recipient’s perspective respectively, with the emphasize on the mechanism used. The working definition of knowledge sharing, knowledge reuse, and knowledge transfer used in this thesis are listed as follows by considering different emphasis:

 Knowledge sharing is the process in which the knowledge sender contributes his/her knowledge to the recipient and initiates the knowledge movement from the sender to the recipient. The focal actor is the knowledge sender.

 Knowledge reuse is the process in which the recipient seeks and acquires the knowledge from the sender (different from the recipient herself/himself), initiates the knowledge movement from the sender to the recipient and applies the knowledge received. The focal actor is the knowledge recipient and the focus is on the reuse of knowledge from the sender, rather than reuse of the recipient’s own knowledge.

 Knowledge transfer is the knowledge movement from the sender to the recipient. The focus is on the mechanism used to facilitate the knowledge movement.

Mechanisms in knowledge transfer (i.e., including both knowledge sharing and knowledge reuse in this thesis) describe how and through what intermediate steps certain

knowledge is delivered following a set of initial conditions from the knowledge sender to the recipient, including the methods, procedures, or processes involved in knowledge movement (Chai et al., 2003). The success of knowledge transfer depends largely on the

knowledge is delivered following a set of initial conditions from the knowledge sender to the recipient, including the methods, procedures, or processes involved in knowledge movement (Chai et al., 2003). The success of knowledge transfer depends largely on the

In document Knowledge sharing and reuse in product-service systems with a product lifecycle perspective (sivua 43-52)